An iterative layout optimization design method for centralized photovoltaic power stations that incorporates multi-dimensional and multi-objective constraints

To address the limitations of multi-constraint deep coupling and single-value optimization in the layout design of centralized photovoltaic power stations in complex terrains, an iterative layout optimization design method integrating multi-dimensional and multi-objective constraints is proposed. A three-layer integrated constraint system combining hard boundaries, variable regulation, and goal-driven strategies was constructed. The full-parameter grid traversal and Pareto non-dominated sorting strategies are introduced. Parameter enumeration and multi-objective screening were carried out based on terrain analysis and power generation simulation. The results show that the optimized maximum capacity scheme reaches 79.8 MWp, an increase of 16.5% compared to the initial design; the highest power generation scheme has a first-year power generation of 112.7 million kWh, an increase of 12.0%; and the lowest levelized cost of electricity scheme drops to 0.283 yuan/kWh, a reduction of 10.2%. The results indicate that this method can effectively reveal the coupling paths among the three layers of constraints, providing an optimization framework and quantitative basis for the multi-objective collaborative decision-making of capacity and power generation cost in the layout design of centralized photovoltaic power stations in complex terrains.